Distinguishing manipulated stocks via trading network analysis

► We construct a trading network for each stock in a one-year period. ► We find that node degree and strength both have power-law tails for all trading networks. ► Comparing with non-manipulated stocks, the manipulated stocks are revealed as different. ► Manipulated stocks have a high lower bound of the power-law tail and high average degree. ► Manipulated stocks have low correlation between the price return and seller-buyer ratio.